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Add Command

Organization
Doist
add-command

Guide for adding new CLI commands or subcommands to todoist-cli. Use when implementing new SDK endpoints, adding subcommands to existing command groups, or extending CLI functionality.

Overview

PublisherDoist
Repositorytodoist-cli
Skill nameadd-command
Stars
323
Forks
18
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Doist on GitHub. Read the source before you install it.

Installation

Install the Add Command AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Doist/todoist-cli/tree/main/.agents/skills/add-command
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Doist/todoist-cli.git /tmp/todoist-cli
mkdir -p .claude/skills
cp -r /tmp/todoist-cli/.agents/skills/add-command .claude/skills/add-command
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Add Command in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Add Command on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Add Command is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Adding a New CLI Command or Subcommand

Follow this checklist when adding new commands. Each step references the exact file to modify.

1. Mock API (src/__tests__/helpers/mock-api.ts)

Add a mock for each new SDK method in createMockApi(). Place it in the correct entity group.

  • List/read methods: .mockResolvedValue({ results: [], nextCursor: null }) or appropriate empty default
  • Mutation methods: vi.fn() (no default return needed)

2. Spinner Messages (src/lib/api/core.ts)

Add an entry to API_SPINNER_MESSAGES for each new SDK method.

Color convention:

  • blue — read/fetch operations
  • green — create/join operations
  • yellow — update/delete/archive mutations

3. Read-Only Permissions (src/lib/permissions.ts)

If the new command uses a read-only SDK method (e.g., getXxx, listXxx), add it to the KNOWN_SAFE_API_METHODS set. This set uses a default-deny approach: any method not listed is treated as mutating and will be blocked when the CLI is authenticated with a read-only OAuth token (td auth login --read-only).

  • Read-only methods (fetch/list/view): add to KNOWN_SAFE_API_METHODS
  • Mutating methods (add/update/delete/archive/move): do NOT add — they are blocked by default, which is the correct behavior

4. Agent-Friendly Design Checklist

Every new command should satisfy these properties. They ensure the CLI works well for both humans and AI agents. See 7 Principles for Agent-Friendly CLIs for background.

  1. Non-interactive by default — All input via flags, positional args, or --stdin. Never use readline, prompt(), or block waiting for TTY input. When a required argument is missing, call cmd.help() and return — don't prompt.

  2. Structured, parseable output — Data commands must support --json (and --ndjson for lists). Results go to stdout, diagnostics to stderr. Spinners auto-suppress when !process.stdout.isTTY (see src/lib/spinner.ts). Exit code 0 on success, non-zero on failure.

  3. Fail fast with actionable errors — Use CliError with a specific error code, a message naming the exact problem, and hints that include correct invocation syntax, valid values, or example commands. Validate all inputs before making API calls.

  4. Safe retries and explicit mutation boundaries — Mutating commands support --dry-run. Destructive + irreversible commands require --yes. Create commands return the entity ID (use isQuiet() for bare ID output for scripting, e.g. id=$(td task add "Buy milk" -q)).

  5. Progressive help discovery — Parent command groups include .addHelpText('after', ...) with 2–3 concrete examples. Every .description() is a clear one-line purpose statement. When a required positional arg is missing, show help via cmd.help().

  6. Composable and predictable structure — Use consistent subcommand verbs (list/view/create/update/delete/browse). Use consistent flag names across entities (--project <ref>, --json, --dry-run, --yes, --limit, --cursor, --all). Support --stdin for text content where applicable (see readStdin() in src/lib/stdin.ts).

  7. Bounded, high-signal responses — List commands use paginate() from src/lib/pagination.ts with --limit <n>, --cursor, and --all flags. When results are truncated, formatNextCursorFooter() tells the user how to fetch more. JSON output uses formatJson() or formatPaginatedJson() to return essential fields by default, passing the --full flag for complete output.

5. Command Implementation (src/commands/<entity>/)

Commands with multiple subcommands use a folder-based structure:

src/commands/<entity>/
  index.ts          # registerXxxCommand — creates parent cmd, wires subcommands
  list.ts           # async function listXxx(...) — one file per subcommand
  view.ts           # async function viewXxx(...)
  create.ts         # async function createXxx(...)
  helpers.ts        # shared constants/utilities used by multiple subcommands (optional)
  • index.ts: Imports all subcommand handlers, creates the Commander tree, exports registerXxxCommand
  • Subcommand files: Export one async action handler + any option interfaces. Use ../../lib/ for lib imports. No Commander imports (only index.ts uses Commander).
  • helpers.ts: Only needed when multiple subcommands share a utility/constant.

Single-subcommand commands (e.g., add.ts, today.ts) remain as flat files.

Adding a subcommand to an existing command

  1. Create a new file src/commands/<entity>/<action>.ts with the handler function
  2. Import and wire it in src/commands/<entity>/index.ts

Flag conventions

Command typeFlags
Read-only--json (and --ndjson for lists)
Mutating (returns entity)--json (use formatJson), --dry-run
Mutating (no return)--dry-run
Destructive + irreversible--yes, --dry-run
Reversible (archive/unarchive)--dry-run (no --yes)
List (paginated)--limit <n>, --cursor, --all, --json, --ndjson
List (non-paginated)--json, --ndjson

The --quiet / -q flag suppresses success messages on mutations. Create commands in quiet mode print only the bare entity ID for scripting (e.g., id=$(td task add "Buy milk" -q)).

Error handling

Always use CliError from src/lib/errors.ts instead of bare throw new Error(...). This ensures structured error output in JSON mode and consistent formatting in text mode.

typescript
import { CliError } from '../../lib/errors.js'

throw new CliError('ERROR_CODE', 'User-facing message', ['Optional hint'])

When adding a new error code, add it to the ErrorCode type in src/lib/errors.ts under the appropriate category. The type provides intellisense for known codes while accepting any string for dynamic codes.

To make errors actionable for agents:

  • The message must name the specific problem (not generic "invalid input")
  • The hints array should include at least one of: correct invocation syntax, valid values, or a working example command
  • Validate all flag constraints and input early — before any API calls. If flags conflict, throw CliError('CONFLICTING_OPTIONS', ...) immediately

ID resolution

  • resolveXxxRef(api, ref) — when the user knows the entity by name (projects, tasks, labels). Add new wrappers in refs.ts — resolveRef is private.
  • lenientIdRef(ref, 'entity') — when there is no list endpoint for lookup, or the user can't access the entity yet (e.g., comments, reminders, joining an unjoined project)
  • Context-scoped resolvers (resolveSectionId, resolveParentTaskId, resolveWorkspaceRef) — when resolving a name within a parent context (e.g., a section name within a specific project). Each has custom logic in refs.ts.

Subcommand registration pattern

typescript
const myCmd = parent
    .command('my-action [ref]')
    .description('Do something')
    .option('--json', 'Output as JSON')
    .option('--dry-run', 'Preview what would happen without executing')
    .action((ref, options) => {
        if (!ref) {
            myCmd.help()
            return
        }
        return myAction(ref, options)
    })

The variable assignment (const myCmd = ...) is needed so the .action() callback can call myCmd.help() when the argument is missing.

Help text quality:

  • Parent command groups (the registerXxxCommand function) should include .addHelpText('after', ...) with 2–3 concrete invocation examples
  • Every .description() string should be a clear one-line purpose — agents read this to decide which subcommand to call
  • The if (!ref) { cmd.help(); return } pattern ensures the command never blocks when a required argument is missing

6. Accessibility (src/lib/output.ts)

The CLI supports accessible mode via isAccessible() (checks TD_ACCESSIBLE=1 or --accessible flag). When adding output that uses color or visual elements, consider whether information is conveyed only by color or decoration.

When to add accessible alternatives

  • Color-coded status/severity: If color conveys meaning (e.g., green=good, red=bad), add a text prefix or label in accessible mode so the meaning is available without color. Example: formatHealthStatus adds [+], [!], [!!] prefixes.
  • ASCII art / visual bars: Omit entirely in accessible mode — screen readers read each character individually (e.g., ====---- becomes "equals equals equals equals dash dash dash dash"). Show only the numeric value instead.
  • Decorative symbols: Stars, checkmarks, or icons used alongside color should have text equivalents. Example: favorites get ★ only in accessible mode since the yellow color already signals it visually.

When you don't need to do anything

  • Text that is already descriptive: Status names like ON_TRACK, COMPLETED are self-explanatory — color just reinforces them. Still consider adding indicator prefixes for severity.
  • Plain numbers and dates: Already accessible.
  • Dim/styled labels: chalk.dim() for secondary info is fine — screen readers ignore styling.

Pattern

typescript
import { isAccessible } from '../lib/output.js'

// For color-coded values: add text prefix in accessible mode
const a11y = isAccessible()
const prefix = a11y ? '[!] ' : ''
console.log(chalk.yellow(`${prefix}AT_RISK`))

// For visual bars: skip entirely in accessible mode
if (isAccessible()) {
    console.log(`${percent}%`)
} else {
    console.log(`[${'='.repeat(filled)}${'-'.repeat(empty)}] ${percent}%`)
}

If adding a new shared formatter to output.ts, use Record<ExactType, ...> rather than Record<string, ...> so the compiler catches missing variants.

7. Tests (src/__tests__/<entity>.test.ts)

Follow the existing pattern: mock getApi, use program.parseAsync().

Always test:

  • Happy path (correct output, correct API call)
  • INVALID_REF rejection for lenientIdRef commands (plain text like "Planning" should fail)
  • --dry-run for mutating commands (API method should NOT be called, preview text shown)
  • --json output where applicable

8. Skill Content (src/lib/skills/content.ts)

Update SKILL_CONTENT with examples for the new command. Update relevant sections:

  • Command examples in the entity's ### Section block
  • Quick Reference if adding a top-level command
  • Mutating --json list if the command returns an entity
  • --dry-run list if applicable

9. Sync Skill File

After all code changes are complete:

bash
npm run sync:skill

This builds the project and regenerates skills/todoist-cli/SKILL.md from the compiled skill content. The regenerated file must be committed. CI will fail (npm run check:skill-sync) if it is out of sync.

10. Verify

bash
npm run type-check
npm test
npm run check

Frequently asked questions

What does the Add Command AI skill do?

Guide for adding new CLI commands or subcommands to todoist-cli. Use when implementing new SDK endpoints, adding subcommands to existing command groups, or extending CLI functionality.

Why use Add Command on TypingMind?

Because you install it once and use it with any model. Add Command is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Add Command in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Doist/todoist-cli/tree/main/.agents/skills/add-command. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Add Command?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Add Command?

As many as you like. As long as a model supports skills, you can use Add Command with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Add Command AI skill free?

Yes. It is published on GitHub by Doist under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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